Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Enterprises are beginning to deploy AI agents. However, if organizations plan to deploy agentic ecosystems at scale and improve employee acceptance, they might consider treating AI agents as tools working in the background to avoid intimidating employees who think they have to know how to use these tools.  Dorit Zilbershot, vice president of AI and Innovation at ServiceNow, told VentureBeat that employees don’t have to know if teams of AI agents are working in the background.   “There’s so much AI around us that we’re not even aware, and that’s how we are thinking about AI agents in ServiceNow,” Zilbershot said. “It should just work. As an employee, I shouldn’t care if AI agents are in the background.” Zilbershot said employees become “managers” of AI agents in that they just need to do their regular work. The agents are automatically triggered to finish tasks.  Enterprises have begun embracing AI agents and exploring how to deploy them at scale, even as generative AI deployment in enterprises has fallen slightly. Zilbershot said ServiceNow’s generative AI platform, Now Assist, is the company’s “fastest-growing product to date.” Now Assist launched a library of AI agents for customers in September.  AI agents could ideally automate many workflows. This could include sales or product roadmaps, where one agent can encode customer information, another categorizes it and yet another informs an employee of a change in status. Zilbershot said agents don’t replace human employees, they take some busy work away, so the only time humans have to pay attention to an agent is if there’s an agent who’s supposed to interact with them. ServiceNow CEO Bill McDermott told VentureBeat in a separate interview that generative AI, particularly applications around agents, “has grown beyond our expectations.” “We’ve mastered the flow of work and governance, and we’re building agents solving unique problems,” McDermott said. “AI will be in every product we have.” As AI agents grow in popularity, Zilbershot said enterprises need to understand what makes agents work for their organization and employees.  Agents and not assistants Beyond AI agents quietly working in the background, Zilbershot said it’s essential for organizations to understand that agents are not assistants. If not, they risk setting an expectation to users that they will need to learn how to prompt agents instead of letting them work for them autonomously.  “I think we’re doing a little bit of a disservice to our customers when agents function more as assistants, but we don’t change the name,” Zilbershot said. “It just creates a wrong perception in the market and how people approach working with agents.”  Zilbershot added AI agents work best when there are other agents they can interact with, so to handle the expected sprawl of agents, orchestrator agents must be deployed to manage all the agents. ServiceNow ships an orchestrator agent with its Now Assist platform.  Other companies have begun offering enterprises access to use orchestrator agents and build custom AI agents. Crew AI launched an agentic platform this month, while Asana released an agent creator specifically for workflows.  Partnership with Nvidia To expand on its agentic ecosystem, ServiceNow announced it will begin building off-the-shelf AI agents using Nvidia’s NIM Agent Blueprint.  Zilbershot said using the NIM Agent Blueprint helps ServiceNow build more agents at the volume they feel is needed to make agents more efficient. “We’re expanding our ecosystem since there can be a limit to how much we can build on our own; we want to have a strong partnership with companies like NVIDIA to build native AI agents within the ServiceNow platform,” she said.  The first agent ServiceNow will build with Nvidia is a Vulnerability Analysis for Container Security AI Agent. The agent will automate vulnerability analysis and will be available on ServiceNow’s agent platform in 2025.  Zilbershot said the work with Nvidia will be just the first of many possible partnerships ServiceNow will enter into to expand AI agents.  source

By Daniel Wilson ( October 25, 2024, 8:29 PM EDT) — A Court of Federal Claims judge has tossed a dispute over the scope of the U.S. Department of Justice’s corrective action on an information technology task order, saying the case fell within a statutory bar on most task order-related protests…. Law360 is on it, so you are, too. A Law360 subscription puts you at the center of fast-moving legal issues, trends and developments so you can act with speed and confidence. Over 200 articles are published daily across more than 60 topics, industries, practice areas and jurisdictions. A Law360 subscription includes features such as Daily newsletters Expert analysis Mobile app Advanced search Judge information Real-time alerts 450K+ searchable archived articles And more! Experience Law360 today with a free 7-day trial. source

InformationWeek is part of the Informa Tech Division of Informa PLC This site is operated by a business or businesses owned by Informa PLC and all copyright resides with them. Informa PLC’s registered office is 5 Howick Place, London SW1P 1WG. Registered in England and Wales. Number 8860726. source

Edge computing, fueled by AI, represents a new evolutionary phase in digital transformation. For some companies, this convergence is already driving business, and in the EU specifically, distributed open marketplace Europe, or DOME, will help CIOs get on the right path. source

By Dorothy Atkins ( October 25, 2024, 8:48 PM EDT) — A man accused by OpenAI of preventing the ChatGPT-maker from registering its name as a trademark urged the Ninth Circuit on Friday to vacate an injunction blocking him from using the “Open AI” mark while his case is pending, arguing he’s the mark’s senior holder and calling the injunction “extraordinary and unprecedented.”… Law360 is on it, so you are, too. A Law360 subscription puts you at the center of fast-moving legal issues, trends and developments so you can act with speed and confidence. Over 200 articles are published daily across more than 60 topics, industries, practice areas and jurisdictions. A Law360 subscription includes features such as Daily newsletters Expert analysis Mobile app Advanced search Judge information Real-time alerts 450K+ searchable archived articles And more! Experience Law360 today with a free 7-day trial. source

Organizations collect and process numerous types of data with varying levels of sensitivity. All employees must understand the nature of the data they come into contact with and how it should be classified and protected. A guide to understanding data handling Every organization collects and processes data as part of normal operations, and all data has the potential to contain sensitive information. This may include personally identifiable information, such as names, addresses, social security numbers, and banking account numbers, which could be used by a malicious third-party to identify consumers or employees. Other types of sensitive data include confidential internal company information like sales figures, client lists, or intellectual property. The privacy of this data must be protected to maintain regulatory compliance and prevent harm. Anyone who comes into contact with sensitive data must understand how to properly handle and secure it to prevent exposure or unauthorized access. Key elements of a robust data handling policy With a data handling policy, businesses can ensure the safe and effective processing of sensitive information. Such a policy is essential for maintaining data integrity and supporting the overall success and sustainability of the organization. A company’s data handling policy must include guidelines on data collection, storage, use, and disposal while protecting against breaches and unauthorized access. For example, a policy needs to outline measures for access limitation. Access to sensitive data must be limited to employees who need it to perform a specific job function. Access should be terminated as soon as that need expires. To aid in incident response, sensitive data access must be logged to keep track of who has access to sensitive data and why, when data was accessed and by whom, and any changes that were made. It is also necessary to have guidelines on security measures. Sensitive data must be stored properly in locations secured with adequate access controls and encryption. Data storage systems must be protected from unauthorized access and tampering with physical security measures such as locked doors and security cameras, as well as technological security controls like firewalls and antivirus software. All employees are responsible for using strong passwords to prevent unauthorized users from compromising their accounts to access confidential data. Employees must also apply recommended security updates and software patches to any systems used to access data and must protect systems with company-issued or approved antivirus software. In addition, the policy should account for the secure disposal of data. Sensitive data must be disposed of according to all applicable laws and standards. Before disposing of physical media containing sensitive data, it must be altered or destroyed to ensure data recovery is impossible. Enhance your organization’s data handling measures with this seven-page policy, available for download at TechRepublic Premium for only $9. source

 Welcome to the new episode of the TNW Podcast — the show where we discuss the latest developments in the European technology ecosystem and feature interviews with some of the most interesting people in the industry. In today’s special episode, we’re happy to present an interview with Anita Schjøll Abildgaard, co-founder and CEO at Iris.ai. The startup has been around for almost a decade and saw several significant pivots, while Anita and the team have been through all the highs and lows imaginable, including balancing on the brink of bankruptcy. Anita and Andrii talked about it all, as well as the future of academic publishing, the prospects of generative AI, the inconvenience of chat interfaces, and much more. Here are the links for this episode: Music and sound engineering for this podcast are by Sound Pulse. Feel free to email us with any questions, suggestions, and opinions at [email protected]. source

Tech mogul Elon Musk on Thursday filed a lawsuit against OpenAI and its CEO Sam Altman, claiming the maker of generation AI juggernaut ChatGPT violated its founding mission to develop artificial intelligence safely and in an open-source environment. Musk, who was a founder of OpenAI in 2015 along with Altman and Greg Brockman, left the company in 2018 after saying the technology was “potentially more dangerous than nukes.” After Musk’s departure, OpenAI restructured and formed a for-profit arm, gaining major backing from Microsoft, which pledged more than $10 billion to bolster GenAI efforts. The lawsuit also takes aim at the company’s efforts with artificial general intelligence (AGI), which would advance AI research to create human-like intelligence and the ability to self-teach. “To this day, OpenAI, Inc.’s website continues to profess that its charter is to ensure that AGI benefits all of humanity. In reality, however, OpenAI, Inc. has been transformed into a closed-source de facto subsidiary of the largest technology company in the world: Microsoft,” according to the lawsuit. OpenAI’s Altman was briefly fired by its board of directors in November. Just days later after Microsoft intervened, Altman was reinstated, and new board members were named. Microsoft scored a non-voting, “advisory” seat on the board. Related:OpenAI’s Dysfunctional Thanksgiving: 5 Key Players in Coup Drama “Under its new Board, [OpenAI] is not just developing but is actually refining an AGI to maximize profits for Microsoft, rather than for the benefit of humanity,” the lawsuit stated. Musk’s lawsuit marks the latest in a string of legal woes for Open AI, including other lawsuits concerning the company’s use of copyrighted material and an ongoing investigation by the Federal Trade Commission focused on its investments and partnerships. Last year, Musk signed an open letter alongside many technology luminaries calling for a pause on GenAI research. That didn’t stop Musk from launching his own GenAI service, Grok, a large language model trained on posts from Musk’s X platform, (formerly Twitter). Manoj Saxena, founder and chairman of the Responsible AI Institute (RAI Institute), tells InformationWeek in an interview that Musk’s lawsuit could force a very important conversation. “I do believe that deep inside, Elon has a real point of view and concern,” Saxena says. “I saw it both as a brilliant and a reckless move to launch ChatGPT. There’s no doubt it was the ‘iPhone moment’ of the AI industry. But there are still a lot of parts that need to be put in place and as messy as it is, this is a conversation that needs to be had.” Related:FTC GenAI Probe Hits Google, Amazon, OpenAI, Microsoft and Anthropic Saxena likens AI safety to the car industry’s history creating safeguards. “But in this case, we don’t have 50 years,” he warns. InformationWeek has reached out to OpenAI, Microsoft, and Musk’s attorneys and will update with any response. source

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More A new study reveals that generative AI has rapidly transformed from an experimental technology to an essential business tool, with adoption rates more than doubling in 2024.  The research, conducted by AI at Wharton, a research center at the Wharton School of the University of Pennsylvania, in partnership with GBK Collective, provides a comprehensive look at AI’s integration across American businesses. The research team surveyed more than 800 enterprise decision-makers across the United States, examining AI adoption patterns, investment trends, and organizational impacts. The study, titled “Growing Up: Navigating Gen AI’s Early Years,” compared data from 2023 to 2024, tracking changes in usage patterns, departmental adoption, and employee attitudes. Key Findings: • Weekly AI usage among business leaders surged from 37% to 72% • Organizations reported a 130% increase in AI spending since 2023 • 72% of companies are planning additional AI investments in 2025 • 90% of leaders now believe AI enhances employee skills (up from 80%) • Concerns about AI-related job displacement decreased from 75% to 72% • 58% of organizations rated AI’s performance as “great” “The most interesting things that come out of the survey is this snapshot of how corporates are feeling, thinking and implementing Gen AI, and how that is changing quite rapidly,” Stefano Puntoni, Sebastian S. Kresge Professor of Marketing at the Wharton School and co-director of AI at Wharton told VentureBeat. “This year, what we’re seeing is that people are less curious, they are more excited, they’re less scared and there is a more belief that these are tools that are going to augment human expertise.” Investment surge for enterprise AI is a ‘gold mine’ for consultants The research shows a dramatic increase in organizational spending on generative AI, with over 40% of companies now investing more than $10 million in the technology. This represents a significant shift from the previous year when the typical investment range was between $1-5 million. What is perhaps even more interesting than the rise in spending, is understanding where the money is going. “About a third of the money is spent on tech,” explained Puntoni. “But that’s actually a minority of all the money that is pouring into Gen AI.”  The remaining investment is distributed across training and upskilling the existing workforce, onboarding new employees and consulting services. While much of the hype and news in generative AI in 2024 has been about the technology, that’s not the differentiator for many enterprises at this point. “The technology itself is more or less a commodity. meaning, you know, my ChatGPT is as good as your ChatGPT and so the differentiation is largely going to come from the integration of the technology and business processes,” he said. “There’s no template, there’s no blueprint,  people will have to experiment and learn.” Puntoni actually expects that consultants, at least in the short term, will be the big winners in the AI gold rush. In his view, the technology part of generative AI is increasingly becoming commoditized. “I think we’re going to see a protracted period of experimentation, learning new business models and new ways of organizing business functions,” Puntoni said. “It’s a gold mine for consultants And I think this is not going to run out of gold anytime soon.” Small and mid-sized companies lead the way in AI An unexpected finding reveals that smaller organizations are currently ahead in AI adoption compared to their larger counterparts. The study defines smaller organizations as those with revenue between $50 million to $250 million and mid-sized as $250 million to $2 billion. “We still see a difference between smaller organizations and large organizations in reported adoption, as well as less restrictive uses within the organization for experimentation,” Jeremy Korst, Partner with GBK Collective, told VentureBeat.  Korst suggests this could lead to interesting competitive dynamics. That is if the smaller organizations are actually able to find not only cost efficiencies and productivity, but new business models and capabilities, overall competition could increase. Korst said in that situation smaller groups might be able to compete differently and more effectively with some of their larger organizations. What organizations should be doing now to improve enterprise AI outcomes Despite the increased adoption, organizations face several challenges in implementing AI effectively. The study highlights issues around data governance and security, with concerns about unintended data leakage within organizations even when using enterprise-grade AI tools. The research also indicates that while the adoption curve for generative AI has been unprecedented in its speed, organizations are now entering a more mature phase focused on practical implementation and return on investment “I think that organizations ought to be learning, I don’t think there is a way in which you’re going to be successful in the future unless you make a concerted, serious effort to see how this technology can help you,” Puntoni said. source